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Cluster‐analysis attack against a PRivAte Web solution (PRAW)

Yuval Elovici (Deutsche Telekom Laboratories, Ben‐Gurion University of the Negev, Beer‐Sheva, Israel)
Bracha Shapira (Department of Information Systems Engineering, Ben‐Gurion University, Beer‐Sheva, Israel)
Adlay Meshiach (Department of Information Systems Engineering, Ben‐Gurion University, Beer‐Sheva, Israel)

Online Information Review

ISSN: 1468-4527

Article publication date: 1 November 2006

430

Abstract

Purpose

The purpose of this paper is to prove the ability of PRivAte Web (PRAW) – a system for private web browsing – to stand possible attacks.

Design/methodology/approach

Attacks on the systems were simulated, manipulating systems variables. A privacy measure was defined to evaluate the capability of the systems to stand the attacks. Analysis of results was performed.

Findings

It was shown that, even if the attack is optimised to provide the attacker's highest utility, the similarity between the user profile and the approximated profile is pretty low and does not enable the eavesdropper to derive an accurate estimation of the user profile.

Research limitations/implications

One limitation is the “cold start” problem – in the current version, an observer might detect the first transaction, which is always a real user transaction. As a remedy for this problem, the first transaction will be randomly delayed and a random number of fake transactions played before the real one (according to Tr). Another limitation is that PRAW supports only link browsing, originated in search engine interactions (since it is the most common interaction on the web. It should be extended to include concealment of browsing to links originating in the “Favourites” list, that users tend to browse regularly (even a few times a day) for professional or personal reasons.

Practical implications

PRAW is feasible and preserves the privacy of web browsers. It is now undergoing commercialisation to become a shelf tool for privacy preservation.

Originality/value

The paper presents a practical statistical method for privacy preservation and proved that it is standing possible attacks. Methods usually proposed for this problem are not statistical, but cryptography oriented, and are too expensive in processing‐time to be practical.

Keywords

Citation

Elovici, Y., Shapira, B. and Meshiach, A. (2006), "Cluster‐analysis attack against a PRivAte Web solution (PRAW)", Online Information Review, Vol. 30 No. 6, pp. 624-643. https://doi.org/10.1108/14684520610716135

Publisher

:

Emerald Group Publishing Limited

Copyright © 2006, Emerald Group Publishing Limited

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